关键词: 智能网联自动驾驶车辆, 偶发事故, 元胞自动机, 人机混驾交通流

Abstract:

With the ongoing development of integrated vehicle-road-cloud systems, mixed traffic flow composed ofhuman-driven vehicles (HDVs) and connected and autonomous vehicles (CAVs) is expected to become the dominantform of future transportation. To explore the influence mechanism of CAV human-like driving strategy and sensinginformation capability on human-machine mixed driving traffic flow under occasional accident, this paper improvedthe cellular automata rules under the framework of the KKW (Kerner-Klenov-Wolf) model, introduced the synchroni⁃zation factor to consider the CAV human-like driving strategy, and constructed the HDV and CAV car-followingrules for different following modes. Considering the lane-changing demand in accident scenarios, a multi-lane dis⁃cretionary lane-changing strategy incorporating the lane preference of HDVs and CAVs was constructed, along witha mandatory lane-changing rule for CAVs based on lane-changing pressure. Sensitivity analysis was conducted ondifferent lane-changing pressure parameters. Through numerical simulations, the effects of varying traffic volume,CAV penetration rate, CAV perception range of accident information, and CAV human-like driving strategies onmixed traffic flow were analyzed. The results show that the increase of CAVs can effectively alleviate the congestionof traffic flow after occasional accident and limit the spatial and temporal scope of congestion, and the average speedand average traffic volume of the low traffic volume are increased by 11. 74% and 6. 32%, respectively, when CAVpenetration rate is increased from 0 to 1. The enhancement is lower than that of medium and high traffic volume. Inthe case of medium and high traffic volume with CAV penetration rate greater than 0. 4, with the increase of CAVaccident information sensing range, the congestion space in the merging area is gradually dispersed, and traffic effi⁃ciency is improved. With the transition of the CAV human-like driving strategy from aggressive to conservative, theflow of the human-machine mixed driving traffic flow is gradually reduced, and the range of slow queues expands,traffic congestion gradually worsens, and the trend of speed fluctuations in each lane gradually converges over time.

Key words: connected and autonomous vehicles, occasional accident, cellular automata, human-machine mixeddriving traffic flow